کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
482136 | 1446206 | 2007 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Developing effective meta-heuristics for a probabilistic location model via experimental design
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
علوم کامپیوتر (عمومی)
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
This article employs a statistical experimental design to guide and evaluate the development of four meta-heuristics applied to a probabilistic location model. The meta-heuristics evaluated include evolutionary algorithm, tabu search, simulated annealing, and a hybridized hill-climbing algorithm. Comparative results are analyzed using ANOVA. Our findings show that all four implementations produce high quality solutions. In particular, it was found that on average tabu search and simulated annealing find their best solutions in the least amount of time, with relatively small variability. This is especially important for large-size problems when dynamic redeployment is required.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: European Journal of Operational Research - Volume 177, Issue 1, 16 February 2007, Pages 83–101
Journal: European Journal of Operational Research - Volume 177, Issue 1, 16 February 2007, Pages 83–101
نویسندگان
Hari K. Rajagopalan, F. Elizabeth Vergara, Cem Saydam, Jing Xiao,